Description
Summary AI Engineer Location: Coimbatore Experience: 3 - 5 years Type: Full-time Summary: We're building AI-powered intelligence workflows that connect multiple enterprise systems and surface real-time insights where teams need them. We're looking for an engineer with solid hands-on experience who can independently design, build, and ship production-grade GenAI solutions - from agentic workflows to end-to-end API integrations - working directly alongside a senior AI architect. You'll own workstreams, make technical decisions on architecture and integration patterns, and bring full-stack engineering experience that shapes how we build - not just execute tasks handed to you. Roles & Responsibilities: Design, build, and deploy intelligent single and multi-agentic applications using LLMs - task decomposition, planning, and autonomous execution Build full-stack AI-powered applications - backend APIs, frontend interfaces, and the integration layer connecting them to enterprise data systems Develop and own end-to-end AI-powered workflows integrated with backend systems, APIs, and data pipelines across cloud platforms Build and iterate on RAG pipelines - embeddings, vector databases, retrieval logic, and prompt design Prototype and ship PoCs using AI agent frameworks (LangChain, LangGraph, LlamaIndex, or equivalent) Integrate AI solutions across multiple enterprise platforms and APIs using REST, JSON, and cloud services Write clean, production-ready code with documentation, error handling, and maintainability standards Translate business requirements into working GenAI solutions independently with minimal hand-holding Bring in best practices - CI/CD, testing, observability - and help raise the bar for the team Required Skills: 3–5 years of software engineering or AI engineering experience Strong Python proficiency - production code, not just scripts Full-stack development experience - backend APIs, frontend, and the integration layer connecting them Proven experience building and shipping GenAI or LLM-powered applications end-to-end End-to-end API integration experience across multiple systems Cloud platform experience - AWS, Azure, or GCP Experience with AI agent frameworks - LangChain, LangGraph, LlamaIndex, or equivalent Strong debugging and problem-solving mindset - owns failures end-to-end Good to have Skills: Data engineering experience - ETL pipelines, data warehouses (Snowflake, BigQuery, Redshift), or similar RAG pipeline experience - embeddings, vector DBs, retrieval and reranking Automation or integration platform experience - code or no-code Containerization and deployment - Docker, CI/CD pipelines MCP (Model Context Protocol) or agentic tool-use patterns Experience in a fast-moving startup or consulting environment